Reduce Loan Drop out

The Challenge

It is one thing to uncover facts about your customers long after they have already signed up for your services. But think of how powerful it could be to develop real-time insights into individual prospects as they make their way through the sales process. Better yet, consider the powerful effect of using these insights to develop and implement effective customer-acquisition strategies, with personalized offers that ensures that customers move from consideration to purchase. AI can help derive insights from data to help organizations acquire customers, automate decision making, reduce customer acquisition costs and risks.

About the Company

The Solution

40% of consumers abandon onboarding processes when opening a new banking relationship. CyborgIntell can improve customer acquisition and reduce cost. With iTuring, preventing abandonment during the onboarding process becomes simple. iTuring understands why customers have dropped off during onboarding historically and provides accurate predictions on which prospects are likely to abandon the onboarding process.

Not only does iTuring accurately predict which customers are most likely to abandon, it also identifies the individual reasons for why each customer is likely to do so during onboarding in real time. This allows you to understand the factors and adjust business processes and provide personalised offers to ensure they sign up.

For the Education Lending Company, CyborgIntell used iTuring to build a “Non-Take Up Model” and identified both customers at risk and the drivers of abandonment. The lending company used the outputs of the model to formulate personalized offers in real time to ensure the customers complete the onboarding process. They also made changes to their product and policy programs to ensure higher onboarding rates and lower acquisition costs.

Highlights

Increased annual revenue by USD 0.6 Million
Improved onboarding (loan take up) rate by 14%
82% model accuracy
120+ new features engineered
At the start of the project - 18% customers were likely to abandon (not take up loan) post loan risk assessment & approval
3 weeks from project start to production-ready application
AI model built in 50 minutes with iTuring AutoML+ and went live within two weeks

Impact

Onboarding Rates

0 %↑

Revenue

$ 0 mn↑

Features Engineered

0 +

Why CyborgIntell

Not only does iTuring provide highly accurate predictions of which customers are likely to abandon, it also provides explanations for why each customer is likely to drop out. This allows business users to better understand their clients churn behaviour and implement actionable and impactful acquisition strategies.

Reduce Loan Drop out